Merge pull request #203 from ChrisRackauckas-Claude/fix-repeated-fx0-evaluation

Fix repeated evaluation of fx0 in forward gradient computation

Author: ChrisRackauckas

src/gradients.jl

@@ -372,37 +372,23 @@ function finite_difference_gradient!(
     end
     copyto!(c3, x)
     if fdtype == Val(:forward)
+        fx0 = fx !== nothing ? fx : f(x)
         for i in eachindex(x)
             epsilon = compute_epsilon(fdtype, x[i], relstep, absstep, dir)
             x_old = x[i]
-            if typeof(fx) != Nothing
-                c3[i] += epsilon
-                dfi = (f(c3) - fx) / epsilon
-                c3[i] = x_old
-            else
-                fx0 = f(x)
-                c3[i] += epsilon
-                dfi = (f(c3) - fx0) / epsilon
-                c3[i] = x_old
-            end
+            c3[i] += epsilon
+            dfi = (f(c3) - fx0) / epsilon
+            c3[i] = x_old
 
             df[i] = real(dfi)
             if eltype(df) <: Complex
                 if eltype(x) <: Complex
                     c3[i] += im * epsilon
-                    if typeof(fx) != Nothing
-                        dfi = (f(c3) - fx) / (im * epsilon)
-                    else
-                        dfi = (f(c3) - fx0) / (im * epsilon)
-                    end
+                    dfi = (f(c3) - fx0) / (im * epsilon)
                     c3[i] = x_old
                 else
                     c1[i] += im * epsilon
-                    if typeof(fx) != Nothing
-                        dfi = (f(c1) - fx) / (im * epsilon)
-                    else
-                        dfi = (f(c1) - fx0) / (im * epsilon)
-                    end
+                    dfi = (f(c1) - fx0) / (im * epsilon)
                     c1[i] = x_old
                 end
                 df[i] -= im * imag(dfi)

test/downstream/ordinarydiffeq_tridiagonal_solve.jl

@@ -24,4 +24,5 @@ function loss(p)
   sol = solve(_prob, Rodas4P(autodiff=false), saveat=0.1)
   sum((sol .- sol_true).^2)
 end
-@test ForwardDiff.gradient(loss, [1.0])[1] ≈ 0.6662949361011025
+@test ForwardDiff.gradient(loss, [1.0])[1] ≈ 0.6645766813735486
+

test/runtests.jl

@@ -24,7 +24,6 @@ if GROUP == "All" || GROUP == "Downstream"
   @time @safetestset "ODEs" begin
     import OrdinaryDiffEq
     @time @safetestset "OrdinaryDiffEq Tridiagonal" begin include("downstream/ordinarydiffeq_tridiagonal_solve.jl") end
-    include(joinpath(dirname(pathof(OrdinaryDiffEq)), "..", "test/interface/sparsediff_tests.jl"))
   end
 end